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<p>Efficient use of genetic biobank data in support of clinical care would enhance the adoption of personalized medicine. Identification of carriers of medically actionable variants that predispose to cancer enables intensified screening and follow-up to decrease disease risk. Pathogenic variants of the <i>MLH1</i> gene cause Lynch syndrome with a significant risk of developing cancer. Here, we introduce a novel approach for the large-scale screening of biobank SNP-array-based genotyping data to analyze copy-number variants (CNVs). With the method developed, we analyzed the Helsinki Biobank cohort of 121 073 samples and identified 29 <i>MLH1</i> exon 16 deletion (<i>MLH1</i>∆Ex16) carriers, of which five (17%) had not been previously identified in healthcare. Our results demonstrate a high positive predictive value for the identification of <i>MLH1</i>∆Ex16 carriers from genotyping data. The cost-efficient method for detection of CNV carriers from large biobank genotyping cohorts described here facilitates intensified screening and follow-up aiming to cancer prevention.</p>

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Screening of biobank SNP-array genotyping data to detect Lynch syndrome predisposing MLH1 copy number variants

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月26日

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  • Kimmo Ala-Kulju,
  • Olli Carpén,
  • Maarit Lappalainen,
  • Minja Pehrsson

摘要

Efficient use of genetic biobank data in support of clinical care would enhance the adoption of personalized medicine. Identification of carriers of medically actionable variants that predispose to cancer enables intensified screening and follow-up to decrease disease risk. Pathogenic variants of the MLH1 gene cause Lynch syndrome with a significant risk of developing cancer. Here, we introduce a novel approach for the large-scale screening of biobank SNP-array-based genotyping data to analyze copy-number variants (CNVs). With the method developed, we analyzed the Helsinki Biobank cohort of 121 073 samples and identified 29 MLH1 exon 16 deletion (MLH1∆Ex16) carriers, of which five (17%) had not been previously identified in healthcare. Our results demonstrate a high positive predictive value for the identification of MLH1∆Ex16 carriers from genotyping data. The cost-efficient method for detection of CNV carriers from large biobank genotyping cohorts described here facilitates intensified screening and follow-up aiming to cancer prevention.